Engineering
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Predictive Spectrum Analysis — Using ACMA Data to Plan for the Future

Learn how data from the ACMA can reveal usage trends and forecast future spectrum demand.

Predictive Spectrum Analysis — Using ACMA Data to Plan for the Future

Planning ahead with data

Spectrum is a finite resource, and congestion is growing.

The ACMA Register of Radiocommunications Licences (RRL) provides a historical and real time snapshot of spectrum use across Australia.

By analysing this data, it’s possible to anticipate where demand will rise and plan accordingly.


What predictive analysis involves

Predictive spectrum analysis uses machine learning and trend modelling to:

  • Detect growth patterns in licensed frequency bands
  • Forecast congestion or under-utilised regions
  • Recommend optimal frequencies for sustainable expansion

These insights help engineers assign channels today that remain viable in the years ahead.


Turning data into smarter planning

At noIM₃, our predictive models interpret ACMA datasets to align design decisions with future realities.

By combining usage analytics with regulatory constraints, we help clients build networks that are compliant now and adaptable later.

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